Nephrology

An Accurate Charge-Aware Machine-Learning Interatomic Potential for the Reduction of Li-Ion Battery Electrolytes in Solution.

Machine learning interatomic potentials (MLIPs), also known as machine learning force fields (MLFFs), offer scalable means of simulating complex systems and processes at ab initio level accuracy. One such process is the critical yet still poorly understood formation of the solid electrolyte interphase (SEI) at the anode of a Li-ion battery (LIB) during the first charge cycle, where electrochemical...

Natriuretic peptides and cardiac troponins in hypertension and heart failure: A contemporary review of the evidence.

Hypertension is the second leading cause of heart failure (HF), yet strategies for identifying hypertensive individuals at increased HF risk remain limited. Cardiac biomarkers, particularly natriuretic peptides and cardiac troponins, reflect subclinical myocardial stress and injury, and have emerged as promising tools for refining HF risk stratification in hypertensive populations. Experimental, e...

Improved outcomes and donor utilization in heart transplantation with 10 °C static cold storage.

OBJECTIVE: To compare 10 °C static cold storage (SCS) with traditional ice for cardiac allograft preservation, its impact on post-transplant outcomes,...

Correlation between the high-density lipoprotein-to-low-density lipoprotein ratio and contrast-induced acute kidney injury: an analysis based on the in-hospital AKI electronic monitoring system.

BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is a common and serious complication that can occur following angiography procedures. Consid...

Association of allostatic load index with cognitive impairment in high-risk stroke populations.

BACKGROUND: Chronic psychosocial stress induces cumulative physiological dysregulation that accelerates biological aging and contributes to the develo...

The emerging role of antibody-drug conjugates in EGFR-mutant non-small cell lung cancer with acquired resistance to third-generation EGFR tyrosine kinase inhibitors.

Resistance to third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) presents a significant clinical challenge for...

Prospective pilot evaluation of a deep learning model for kidney stone detection on CT using a web-based workflow platform.

Rapid and reliable detection of kidney stones on non-contrast abdominal CT is essential for timely decision-making in emergency radiology. However, ri...

Subtypes of newly diagnosed type 2 diabetes and risk of complications: analysis of electronic health records in the USA.

AIMS/HYPOTHESIS: Data-driven subtyping of type 2 diabetes has not been translated into clinical practice due to the lack of routine fasting glucose an...

Metabolic factor-based machine learning model for mortality prediction in acute hepatitis E: Development and validation from a dual-center cohort.

BACKGROUND: Hepatitis E virus (HEV) infection remains a major cause of liver failure with high short-term mortality, yet predictive models incorporati...

Assessment of GFR Estimation Methods in Patients With Obesity.

CONTEXT: Obesity is an independent risk factor for chronic kidney disease, and accurate estimation of the glomerular filtration rate (GFR) is crucial....

Preoperative prediction of preserved renal parenchymal volume via multilevel CT feature fusion: a proof-of-concept study.

PURPOSE: Accurate preoperative prediction of preserved renal parenchymal volume (RPV) following partial nephrectomy (PN) is critical for individualize...

Machine learning-driven discovery of STAT1 and TRIM22 as immune biomarkers for lupus nephritis: translational insights into diagnosis and pathogenesis.

Machine learning based classification of aggressive and malignant renal tumors from multimodal data.

This study aimed to develop and evaluate a machine learning pipeline using multiphase contrast-enhanced CT images and clinical data to classify renal ...

Prediction of COVID-19 hospitalisation, ICU admission or death following ChAdOx1 vaccination using artificial intelligence: A clinical predictive model from the English RAVEN study.

OBJECTIVES: This study identifies predictors of severe COVID-19 following completion of two-dose primary series of the AZD1222 COVID-19 vaccine, emplo...

The shared mechanisms and potential diagnostic markers for IgA nephropathy and celiac disease.

IgA nephropathy (IgAN) and celiac disease (CeD) are autoimmune disorders characterized by dysregulated immune responses; however, the molecular mechan...

Driver gene mutations and clinical features predict bone metastasis risk in NSCLC: a logistic regression model.

Bone metastasis affects approximately 40% of patients with non-small cell lung cancer (NSCLC), significantly impacting patient survival and prognosis....

NPHS2 Revisited Through 208 Cases and Podocin Complex Modeling.

INTRODUCTION: Steroid-resistant nephrotic syndrome (SRNS) is the leading cause of chronic glomerular disease in individuals under 25 years of age. Bia...

Prognostic models in populations with heart failure: a systematic review and meta-analysis.

BACKGROUND: Heart failure (HF) remains a major cause of morbidity and mortality, highlighting the need for reliable prognostic models. This study prov...

Platelets as immune sensors: monitoring immune dynamics and diagnosing disease states across multiple disorders.

BACKGROUND: Beyond their classical roles in haemostasis and thrombosis, platelets have been recognised as active regulators of immune responses. Howev...

Multimodal machine learning for Cr(Ⅵ) removal and floc settling using image-based floc features and operating parameters.

Electrocoagulation is a promising technique for Cr(Ⅵ) removal from wastewater, but its performance is limited by challenges in adapting to variable co...